1. DSpace standard Data model and DSpace-CRIS
DCAT Discussion: exploring convergence
Andrea Bollini (CTIO)

2. High level comparison DSpace DSpace-CRIS
focus on digital object providing more or less support for the Portland Common Data Model
Communities & collections match the PCDM collection scope & definition
Data model is pre-defined
DSpace-CRIS
allows to manage additional entities to support rich context around the digital object
Out-of-box it provides support for the research domain (CRIS)
Data model is open and configurable: other domains can be managed without change the database or write code

3. DSpace-CRIS in a nutshell
Publications
People Organisations Projects
..more
Better interaction, reputation, dissemination
The University of Hong Kong decides to enhance its Institutional Repository
DSpace-CRIS is released as open source to the community
Today
More than 80 DSpace-CRIS installations running all around the World
Asia | US | Canada | Brasil | Europe | Australia | Africa
Documentation and software available on the DSpace Wiki:

4. Data model Main characteristics of the DSpace-CRIS data model
Publications
Dataset
DSpace
Researcher Pages
Projects
OrgUnits
2nd Level Dynamic Objects
DSpace-CRIS
Main characteristics of the DSpace-CRIS data model
Approach: dynamic, flexible, not hardcoded
Attributes: only a few predefined
Entities: only a few predefined
Uis: all aspects can be defined

5. Main DSpace-CRIS Entities
Managing people:
Tracking author’s identifiers, name variants, career;
Synchronized with ORCID;
Manageable out-of-box by end users
Organisation & projects: Defined as separated entities;
Allow future extensions, specific workflows and editing rules
Other entities:
A single entity characterized by a profile/type (ie: Journal, Prize, Event, etc.;
Each profile has its own set of properties (independently defined)

6. An integrated view of the research, other domains supported!

7. The data model configuration doesn’t require coding!

11. Tabs
Boxes
Fields

12. How to collect the additional data
automatically synchronized with external sources, out-of-box using spreadsheets
manually created during publication / dataset submission
Rich researcher profiles can be automatically imported from the ORCID registry
Rich information can be collected as part of the item submission and moved to the right entity when confirmed
new records can be confirmed / integrated by the administrator
created as DSpace items and automatically converted into the right entity upon validation
managed via UI by administrators

13. Additional DSpace-CRIS benefits
Search & browse all the entites
Global search and specialized section for any entity
Aggregated statistics: by all entity (author, organisation, project, etc.)
Full ORCID integration (push and pull information)
Network visualization
Alert and report about potential duplicate, merge tool for administrators
Metrics framework: allows to store the reference period, the date of collection exposing the information to be shown in the list or used to sort. Ranking, count and aggregation performed automatically
Automatic scanning of external datasource (WoS, Scopus, etc.)

14. ORCID Integration
Create new record - facilitate the creation of new ORCID records for researchers
Connect local profile with the ORCID registry
Lookup the registry
Transfer information from the repository to the ORCID Registry and viceversa
Login via ORCID iD
also for external
co-authors (if liked)

17. Screens
from a recent public installation with basic layout customization at The Hong Kong Polytechnic University

18. http://ira.lib.polyu.edu.hk (link)
Run the latest released version 5.5
Manage people, organisation, publications patents, thesis
Integrated with bibliometric database
Run by the library, integrated with HR, commercial database, etc.

19. Global search across the whole site with highlighting of found terms

20. Narrowing the result by a specific entity type provide further faceting options

21. Dynamic components are contextualized (site level, researcher outputs, researchers, etc.)

22. At the site level the recent submissions are all journal articles

23. Explore Theses: contextualised recent submissions and top viewed

24. At the site level the most viewed item is a Thesis, the second one a Journal article

25. Explore Research Output: contextualised top list, specific browse & search indexes

26. Explore Researchers: different browse & search indexes; different components

27. Beside the metadata the system shows all the available metrics

28. Rank as percentile compared to the other objects in the repository5
Metric value (citation number) linked to an external detail page when provided
Grown tracked locally

30. Link to Google Scholar citations & altmetric badge

31. Link to Google Scholar citations & altmetric badge

32. Links to more detailed record for authors, journals and any related entities

33. Data are organized in
several pages (tabs)

34. Each page is composed by several boxes

35. Each box includes one or more fields
Each box includes one or more fields. Different datatypes are supported to allow storing of photo, text, number, identifiers, link to other entities

36. /cris/rp/details.html?lt=orcid&lv=0000-0002-2312-0318
External identifiers can be used to directly address the profile page without knowing the internal CRIS identifier
/cris/rp/details.html?lt=orcid&lv=
Any type of identifier is allowed (including the ones created locally by the institution – e.g.: staff #)
/cris/rp/details.html?lt=<ext_id>&lv=<ext_value>
This permits an easy and direct integration with other institutional sites (staff directory, etc.)

37. All the objects (publications, projects, etc
All the objects (publications, projects, etc.) linked to a researcher can be automatically included in her profile using dynamic components
Link inverso alle pubblicazioni

38. The metric framework can be applied to any entity – out-of-the-box support of Scopus, Web of Science, PubMed and internal usage statistics for publications and researchers

39. It is possible to explore the collaboration network of a researcher based on your own criteria (co-authoring publications, coinvestigation projects, co-interest, etc.)

40. Once a co-researcher is selected it is possible to see the details of the collaboration

41. Once a co-researcher is selected it is possible to see the details of the collaboration

43. It is also possible to navigate through the hierarchy of organizations

44. All the objects (publications, projects, etc
All the objects (publications, projects, etc.) linked to the organization can be automatically included

45. …including indirect reference (via researchers) and their metrics

46. Internal usage statistics are available at all levels of hierarchy, including the whole repository

47. Internal usage statistics are available at all levels of hierarchy, including the whole repository

48. Internal usage statistics are available to all levels of hierarchy, including the whole repository

49. Thanks for your attention
Andrea Bollini (CTIO)
mobile:
skype: a.bollini
linkedin: andreabollini
orcid: